Hyperspectral image clustering method based on Artificial Bee Colony algorithm

Pixel clustering is a common hyperspectral image processing technique. Its process is to find the appropriate cluster centers and assign each pixel to a center according to a certain metric. Artificial Bee Colony (ABC) algorithm based pattern clustering is proved to have better performance than traditional clustering methods such as K-means. Therefore, studies on hyperspectral image clustering method based on ABC algorithm are done. The target function and feasible solution space are determined, and the complete process is given. The proposed algorithm and other algorithms are compared and analyzed with the use of two sets of real hyperspectral remote sensing data and ground survey results.